Add /dev/nvidiactl to the list of NVIDIA GPU devices. This is to cover the use case where a subset of GPUs are exposed to Docker/Kubernetes; the container might not necessarily see /dev/nvidia0. #22773
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
![copybara-service[bot]](https://avatars.githubusercontent.com/in/44061?s=60&v=4){kind=small}
copybara-service
bot
force-pushed
the
test_657776716
branch
4 times, most recently
from
b4c85af to
8559727
Compare
…r the use case where a subset of GPUs are exposed to Docker/Kubernetes; the container might not necessarily see /dev/nvidia0. Testing: Tested on a A100 16 GPU VM with only 8 GPU exposed to the container. PiperOrigin-RevId: 657801141
copybara-service
bot
force-pushed
the
test_657776716
branch
from
8559727 to
35ba6f7
Compare
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Add /dev/nvidiactl to the list of NVIDIA GPU devices. This is to cover the use case where a subset of GPUs are exposed to Docker/Kubernetes; the container might not necessarily see /dev/nvidia0.
Testing:
Tested on a A100 16 GPU VM with only 8 GPU exposed to the container.